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在食道运动障碍中的人工智能:对高分辨率计量研究的系统审查
Eun Jeong Gong1,2,3, Chang Seok Bang2,3,4, Jae Jun Lee3,5
1Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea.
Journal of medical Internet research
|November 27, 2025
概括
人工智能 (AI) 显著改善了高分辨率食道测量仪 (HRM) 的解释,达到高达97%的准确性. 虽然有望实现标准化诊断和降低成本,但临床翻译需要进一步的验证和监管批准.
科学领域:
- 胃肠病学和肝病学 胃肠学和肝病学
- 医学诊断 医学诊断 医学诊断
- 人工智能在医学中的应用
背景情况:
- 高分辨率食道测量 (HRM) 对于诊断食道运动障碍在10%-15%的失患者中至关重要.
- 目前使用芝加哥分类的HRM解释面临着30%-40%的观察者间变异性挑战.
- 人工智能 (AI) 为自动化和标准化人力资源管理解释提供了潜在的解决方案.
研究的目的:
- 评估当前用于HRM解释的人工智能应用.
- 评估AI的诊断准确性,方法方法和临床验证.
- 探索实施障碍和对胃肠病学实践的现实世界的影响.
主要方法:
- 在PubMed/MEDLINE,Embase,Cochrane图书馆和Web of Science的系统文献搜索到2025年11月.
- 包括人工智能/机器学习对成年食道HRM解释的原始研究研究.
- 对人工智能模型任务,诊断结果,外部验证和实时处理的数据提取;使用QUADAS-2进行质量评估;定性叙事合成.
主要成果:
- 17项研究显示了AI的演变:传统的ML (86.5%-94%准确度),深度学习 (高达97%的分类准确度) 和多式联络方法 (83%-95%准确度,解释时间小于2分钟).
- 人工智能表现出优越的一致性,观察者内部变化率为0%,而人类专家的变化率为15%-30%.
- 发现了关键差距:0%的外部验证,82%的不明确的患者选择偏差和没有监管批准;由于缺乏现实世界的测试,对适用性存在高度担忧.
结论:
- 人工智能对人力资源管理的解释具有变革性的潜力,可以实现高诊断准确度和有前途的标准化诊断.
- 人工智能可以解决专家短缺问题,并通过提高效率来降低成本,但验证和监管批准的重大差距阻碍了临床翻译.
- 未来的优先事项包括多中心验证试验和制定监管途径,以促进AI在临床实践中的采用.
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